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anjakefala

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I think the argument is that for non-scientific usecases, folks don't really need to think about error or significant digits. By focusing on the significand too much laypeople aren't grasping how large and small these numbers are relative to each other.

It's not being put forward as a recommended tool for scientists when reasoning about precise values. It's put forward for laypeople when trying to understand the vastness of the universe.

For example, some apparently 10x engineers were only so because they were allowed to only work on interesting, relatively easy early stage work. The difficult, fiddly work of mopping up the awkward corners was left to other engineers, who were considered 'slow'.

I am someone who loves mopping up the awkward corner cases. For me, this is the most fun part of coding. I think the early design and infrastructure work is actually pretty challenging work. The decisions made at this stage pay dividends later on, in ease of debugging, api goodness, future expendability, etc. I prefer collaborating with senior engineers who are strong and relatively fast with that, and then I help clean-up to facilitate their speed. If everyone is on-board, I am not sure what is wrong with this arrangement.

  Location preference: Vancouver, Canada 
  Remote: Open to
  Willing to relocate: To the US
  Technologies: Python, Bash, R, statistics, strong linux foundation, some exposure to AWS, experience with medical imaging technology and protocols - interested in devops/sre
  Résumé/CV: http://anja.kefala.info/resume.pdf
  Email: anja.kefala@gmail.com

I feel like this is the core of how "Open Software" is aiming to combat this. By removing the consumer-driven model away from software and putting users in closer touch with developers, we are supposedly developing tools together that better fit our needs. Though, OSS arguably is struggling to meet this theoretical ideal, especially with the current lack of support most OSS devs have.

My life improved considerably when I switched from Sublime to vim, Excel to VisiData, Word to LaTeX (though, I am unsure if LaTeX is completely OSS), etc. I invested the time in learning the language of the tool, but it pays off in droves.

I found this to be a very clear and well-structured post. I was not surprised to read that the author is a historian. I especially liked the detail in their process where they automatically update the communal sheet to indicate that the data has already been processed.